Hogg-Huberman strategy with net bias in chaotic discrete-time computational ecosystems

Discusses controlling the chaos of discrete-time computational ecosystems by a reward mechanism with strategies based on net bias. A fixed point caused by the reward mechanism is an optimal point in the sense that all agents get the same pay off from resources. It is shown that, if the number of strategies are greater than two, there are an infinite number of unisolated fixed points where the total amount of payoffs from each resource is equal. Moreover, by computer simulation, we show the effects of strategies on stability and transient behaviors